Abstract
The objectives of this paper are to present, describe, and explain the foundations and the functionalities of a temporal knowledge acquisition and modeling solution workflow, which aims at acquiring temporal knowledge from texts in order to populate a constrained object model. We are using several models for temporal data, one of which is generic and employed as a pivot model between a linguistic representation and a calendar representation. The approach we propose is generic and has been tested against a real use case, in which input data is made of temporal properties defining when a given location (a theater, a restaurant, a shopping center, etc.) is open or closed. Most expressions entered are expressed in intension. Our models provide a core support to the system that linguistically analyses data entries, transforms them into extensive calendar information and allow users to control the quality of the system’s interpretation.
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Faucher, C., Teissèdre, C., Lafaye, JY., Bertrand, F. (2010). Temporal Knowledge Acquisition and Modeling. In: Cimiano, P., Pinto, H.S. (eds) Knowledge Engineering and Management by the Masses. EKAW 2010. Lecture Notes in Computer Science(), vol 6317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16438-5_27
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DOI: https://doi.org/10.1007/978-3-642-16438-5_27
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